diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp
index 0e04eb5cc..320f0b382 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train_adapter.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py
index 1c9be54d4..5ac284746 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train_adapter.py
@@ -832,8 +832,9 @@ def compute_loss(
     batch_idx_train = params.batch_idx_train
     warm_step = params.warm_step
 
-    #texts = batch["supervisions"]["text"]
-    texts = batch["greedy pseudo text"]
+    texts = batch["supervisions"]["text"]
+    print(texts)
+    #texts = batch["greedy pseudo text"]
     token_ids = sp.encode(texts, out_type=int)
     y = k2.RaggedTensor(token_ids).to(device)